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@moduledoc """
This module defines how special metrics like `conversion_rate` and
`percentage` are calculated.
"""
use Plausible.Stats.SQL.Fragments
alias Plausible.Stats.{Base, Query, SQL, Filters}
import Ecto.Query
import Plausible.Stats.Util
@special_metrics [
:percentage,
:conversion_rate,
:group_conversion_rate,
:scroll_depth,
:exit_rate
]
def add(q, site, query) do
Enum.reduce(@special_metrics, q, fn special_metric, q ->
if special_metric in query.metrics do
add_special_metric(q, special_metric, site, query)
else
q
end
end)
end
defp add_special_metric(q, :percentage, site, query) do
total_query =
query
|> remove_filters_ignored_in_totals_query()
|> Query.set(
dimensions: [],
include_imported: query.include_imported,
pagination: nil
)
q
|> select_merge_as([], total_visitors_subquery(site, total_query, query.include_imported))
|> select_merge_as([], %{
percentage:
fragment(
"if(? > 0, round(? / ? * 100, 2), null)",
selected_as(:total_visitors),
selected_as(:visitors),
selected_as(:total_visitors)
)
})
end
# Adds conversion_rate metric to query, calculated as
# X / Y where Y is the same breakdown value without goal or props
# filters.
defp add_special_metric(q, :conversion_rate, site, query) do
total_query =
query
|> Query.remove_top_level_filters(["event:goal", "event:props"])
|> remove_filters_ignored_in_totals_query()
|> Query.set(
dimensions: [],
include_imported: query.include_imported,
preloaded_goals: Map.put(query.preloaded_goals, :matching_toplevel_filters, []),
pagination: nil
)
q
|> select_merge_as(
[],
total_visitors_subquery(site, total_query, query.include_imported)
)
|> select_merge_as([e], %{
conversion_rate:
fragment(
"if(? > 0, round(? / ? * 100, 2), 0)",
selected_as(:total_visitors),
selected_as(:visitors),
selected_as(:total_visitors)
)
})
end
# This function injects a group_conversion_rate metric into
# a dimensional query. It is calculated as X / Y, where:
#
# * X is the number of conversions for a set of dimensions
# result (conversion = number of visitors who
# completed the filtered goal with the filtered
# custom properties).
#
# * Y is the number of all visitors for this set of dimensions
# result without the `event:goal` and `event:props:*`
# filters.
defp add_special_metric(q, :group_conversion_rate, site, query) do
group_totals_query =
query
|> Query.remove_top_level_filters(["event:goal", "event:props"])
|> remove_filters_ignored_in_totals_query()
|> Query.set(
metrics: [:visitors],
order_by: [],
include_imported: query.include_imported,
preloaded_goals: Map.put(query.preloaded_goals, :matching_toplevel_filters, []),
pagination: nil
)
from(e in subquery(q),
left_join: c in subquery(SQL.QueryBuilder.build(group_totals_query, site)),
on: ^SQL.QueryBuilder.build_group_by_join(query)
)
|> select_merge_as([e, c], %{
total_visitors: c.visitors,
group_conversion_rate:
fragment(
"if(? > 0, round(? / ? * 100, 2), 0)",
c.visitors,
e.visitors,
c.visitors
)
})
|> select_join_fields(query, query.dimensions, e)
|> select_join_fields(query, List.delete(query.metrics, :group_conversion_rate), e)
end
defp add_special_metric(q, :scroll_depth, _site, query) do
max_per_session_q =
Base.base_event_query(query)
|> where([e], e.name == "engagement" and e.scroll_depth <= 100)
|> select([e], %{
session_id: e.session_id,
max_scroll_depth: max(e.scroll_depth)
})
|> SQL.QueryBuilder.build_group_by(:events, query)
|> group_by([e], e.session_id)
dim_shortnames = Enum.map(query.dimensions, fn dim -> shortname(query, dim) end)
dim_select =
dim_shortnames
|> Enum.map(fn dim -> {dim, dynamic([p], field(p, ^dim))} end)
|> Map.new()
dim_group_by =
dim_shortnames
|> Enum.map(fn dim -> dynamic([p], field(p, ^dim)) end)
total_scroll_depth_q =
subquery(max_per_session_q)
|> select([], %{})
|> select_merge_as([p], %{
# Note: No need to upscale sample size here since it would end up cancelling out due to the result being an average
total_scroll_depth: fragment("sum(?)", p.max_scroll_depth),
total_scroll_depth_visits: fragment("uniq(?)", p.session_id)
})
|> select_merge(^dim_select)
|> group_by(^dim_group_by)
join_on_dim_condition =
if dim_shortnames == [] do
true
else
dim_shortnames
|> Enum.map(fn dim -> dynamic([_e, ..., s], selected_as(^dim) == field(s, ^dim)) end)
# credo:disable-for-next-line Credo.Check.Refactor.Nesting
|> Enum.reduce(fn condition, acc -> dynamic([], ^acc and ^condition) end)
end
joined_q =
join(q, :left, [e], s in subquery(total_scroll_depth_q), on: ^join_on_dim_condition)
if query.include_imported do
joined_q
|> select_merge_as([..., s], %{
scroll_depth:
fragment(
"""
if(? + ? > 0, toInt8(round((? + ?) / (? + ?))), NULL)
""",
s.total_scroll_depth_visits,
selected_as(:__imported_total_scroll_depth_visits),
s.total_scroll_depth,
selected_as(:__imported_total_scroll_depth),
s.total_scroll_depth_visits,
selected_as(:__imported_total_scroll_depth_visits)
)
})
else
joined_q
|> select_merge_as([..., s], %{
scroll_depth:
fragment(
"if(any(?) > 0, toUInt8(round(any(?) / any(?))), NULL)",
s.total_scroll_depth_visits,
s.total_scroll_depth,
s.total_scroll_depth_visits
)
})
end
end
# Selects exit_rate into the query, calculated as X / Y, where X is the
# total number of exits from a page (i.e. the number of sessions with a
# specific exit page), and Y is the total pageviews on that page.
defp add_special_metric(q, :exit_rate, site, query) do
total_pageviews_query =
query
|> Query.remove_top_level_filters(["visit:exit_page"])
|> remove_filters_ignored_in_totals_query()
|> Query.set(
pagination: nil,
order_by: [],
metrics: [:pageviews],
include_imported: query.include_imported,
dimensions: ["event:page"]
)
joined_q =
q
|> join(:left, [], p in subquery(SQL.QueryBuilder.build(total_pageviews_query, site)),
on:
selected_as(^shortname(query, "visit:exit_page")) ==
field(p, ^shortname(total_pageviews_query, "event:page"))
)
if query.include_imported do
joined_q
|> select_merge_as([..., p], %{
exit_rate:
fragment(
"if(? > 0, round(? / ? * 100, 1), NULL)",
p.pageviews,
selected_as(:__internal_visits),
p.pageviews
)
})
else
joined_q
|> select_merge_as([..., p], %{
exit_rate:
fragment(
"if(? > 0, round(? / ? * 100, 1), NULL)",
fragment("any(?)", p.pageviews),
selected_as(:__internal_visits),
fragment("any(?)", p.pageviews)
)
})
end
end
# `total_visitors_subquery` returns a subquery which selects `total_visitors` -
# the number used as the denominator in the calculation of `conversion_rate` and
# `percentage` metrics.
# Usually, when calculating the totals, a new query is passed into this function,
# where certain filters (e.g. goal, props) are removed. That might make the query
# able to include imported data. However, we always want to include imported data
# only if it's included in the base query - otherwise the total will be based on
# a different data set, making the metric inaccurate. This is why we're using an
# explicit `include_imported` argument here.
defp total_visitors_subquery(site, query, include_imported)
defp total_visitors_subquery(site, query, true = _include_imported) do
wrap_alias([], %{
total_visitors:
subquery(total_visitors(query)) +
subquery(Plausible.Stats.Imported.total_imported_visitors(site, query))
})
end
defp total_visitors_subquery(_site, query, false = _include_imported) do
wrap_alias([], %{
total_visitors: subquery(total_visitors(query))
})
end
defp remove_filters_ignored_in_totals_query(query) do
totals_query_filters =
Filters.transform_filters(query.filters, fn
[:ignore_in_totals_query, _] -> []
filter -> [filter]
end)
Query.set(query, filters: totals_query_filters)
end
defp total_visitors(query) do
Base.base_event_query(query)
|> select([e],
total_visitors: scale_sample(fragment("uniq(?)", e.user_id))
)
end
end
|